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5 Teams Aim for the Moon This Year—and the $20 Million Google Lunar XPrize

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The TeamIndus ECA rover. Image Credit: TeamIndus

Though space agencies from the Soviet Union, the United States, and China have notched Moon landings, no private company or organization has ever managed to duplicate the task. No private effort has even managed to achieve a launch manifest for a rocket—until now.

The Google Lunar XPrize is a competition to land a spacecraft on the surface of the Moon, have it travel 500 meters, and provide video and imagery of the whole affair. The prize for being first: $20 million. The second-place team gets $5 million, and another $5 million goes to assorted prizes. 

In 2007, more than 30 teams registered to compete for that $30 million. Today, only five remain. Each one has a launch manifest (a scheduled ride) on one of four different rockets. To remain in the competition and win some part of the $30 million bounty, the missions must launch this year.

Chanda Gonzales-Mowrer, senior director of the Google Lunar XPrize, tells mental_floss, “What we are the most excited about is the fact that all five teams are approaching this challenge in unique ways, and we were thrilled to have five finalist teams come from all parts of the world.”

The race is fraught with perils, and despite having been manifested for flight, even reaching the launch pad will require the full measure of each team’s engineering know-how. Still, the Google Lunar XPrize foundation is confident that this is the year. “We are very optimistic that at least one team will launch by the December 31, 2017 deadline,” says Gonzales-Mowrer.

Meet the five teams to learn more about their mission goals and specs.


An illustration of the Moon Express MX-1E lander approaching the lunar surface. Image Credit: Moon Express

In 2010, Bob Richards, Naveen Jain, and Barney Pell formed Moon Express with the goal of applying the Silicon Valley philosophy of moving fast and iterating to the Moon problem. They’ve certainly applied Silicon Valley dollars, garnering $45 million so far in a fundraising effort that goes far beyond the competition. The company intends to establish a resource mining operation on the lunar surface, seeking such elements as oxygen and hydrogen that might be converted to water, breathable air, and used as an oxidizer for spacecraft propellant. Jain has described the Moon as the “eighth continent,” and he certainly has a point: At 37.9 million square miles, the lunar surface is smaller than Asia but larger than Africa.

The mission is set to launch this year atop a New Zealand-built Electron rocket from the company Rocket Lab USA. The Moon Express lander is called MX-1E, and it will perform a powered landing on the lunar surface, using its thrusters to perform a series of “micro hops” to cross the finish line. The spacecraft will be powered with hydrogen peroxide propellant—the same stuff that’s likely in your medicine cabinet, H2O2. Why hydrogen peroxide? Because hydrogen and oxygen harvested from the Moon might one day be able to be refined to fuel a future Moon Express spacecraft.

Such thinking is in keeping with the competition’s long-term goals, explains Gonzales-Mowrer, which includes stimulating "the larger conversation about building a lunar economy and bringing commercial enterprise to the Moon."


An artist's rendition of the SpaceIL combo lander/hopper. Image Credit: SpaceIL

Like MoonEx, SpaceIL is no garage operation. The nonprofit organization is fueled by a $36 million budget. Their goal isn’t mineral mining, however, but inspiring an “Apollo effect”—that is spurring a STEM renaissance in Israel, where the company is based. To some extent, the competition is a race to be the fourth nation to plant a flag on the Moon, with Japan and India competing against Israel.

SpaceIL was founded by Eran Privman, Yariv Bash, Kfir Damari, and Yonatan Winetraub—a deep bench of electrical and computer engineers. It was the first team in the Google Lunar XPrize to be manifested on a launch vehicle: a SpaceX Falcon 9 rocket. To travel the 500 meters, their spacecraft, which vaguely resembles a frog, will not roll on tracks or wheels, or skip along gently, but rather will make a single, giant hop to the finish line.


A March 2014 test of an Interorbital Systems Neptune rocket with a Synergy Moon payload aboard. Image Credit: Synergy Moon/Interorbital Systems

Led by Nebojsa Stanojevic of Bosnia and Herzegovina, 15 countries are represented on the Synergy Moon team. Their hope is that their success thus far—and hopefully achievements to come—will foster other such cooperative international efforts, and prove what is possible when one approaches the world “with the creative drive of an artist and the problem-solving skills of an engineer,” they say.

Their pair of lunar vehicles are called the Tesla prospector rover and the Tesla surveyor rover. Though Synergy Moon has kept recent details and designs of the rovers close to its chest, in keeping with the artistic and international engagement aspects of the mission, they plan for “tourists, scientists, and prospectors to take control of the rovers for virtual excursions on the Moon,” according to their website. The robots will be launched on a Neptune rocket by Interorbital Systems. Upon arrival at the Moon, a small “tube sat” will deploy from the cruiser to establish communications, and the lander will begin its ascent. Once safely settled in Moon dust, the rovers will get to work, one returning high-resolution images, the other sniffing the lunar regolith for resources for eventual harvest and refinement.


Members of TeamIndus with their lander. Image Credit: XPrize Foundation

Last year Team Indus won a $1 million milestone prize for its lander technology—money that has thrust the privately funded team forward in its likelihood of reaching the lunar surface. This is the only team from India, and, like SpaceIL, they hope their mission will be a sort of robotic ambassador for its country that will pay dividends by engaging and invigorating citizens, private industry, and even the Indian government, whose space agency is already making great strides at Mars. Rahul Narayan, a software engineer and entrepreneur from Delhi, is the mission’s leader.

The Team Indus rover ECA—seen at top—has a passing resemblance to Nintendo’s Robotic Operating Buddy. The vehicle is solar powered, all-aluminum, and has four-wheel drive, and among its scientific payload is a high definition camera made by the French Space Agency. The rover will land autonomously in the Sea of Showers, roll away from the lander platform, link up with Earth, and begin transmitting. It is a straightforward lunar lander and rover—to the extent that it’s possible for any craft operating on the Moon to be described as such.


Hakuto is Japanese for “white rabbit,” and refers to a Japanese story about a rabbit that can be seen in the crater shadows of the moon. The description is apt, too, as the Hakuto rover, shiny and sharp, weighs less than four kilograms, making it the world’s smallest planetary exploration rover.

“To reduce launch cost,” Tomoya Mori of Hakuto tells mental_floss, “we need to make our rover as light and small as possible. At the same time, however, the rover must meet the requirements to successfully accomplish the mission.” They achieved this miniaturization using microrobotics technology and commercial, off-the-shelf products.

Under mission leader Takeshi Hakamada, the mission has forged partnerships with nine players in the aerospace industry, who are assisting with everything from instrumentation to orbital design. Notably, Hakuto will catch a ride to the Moon on the same rocket as Team Indus—an Indian Space Research Organization rocket called the Polar Satellite Launch Vehicle.

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iStock // Ekaterina Minaeva
Man Buys Two Metric Tons of LEGO Bricks; Sorts Them Via Machine Learning
May 21, 2017
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iStock // Ekaterina Minaeva

Jacques Mattheij made a small, but awesome, mistake. He went on eBay one evening and bid on a bunch of bulk LEGO brick auctions, then went to sleep. Upon waking, he discovered that he was the high bidder on many, and was now the proud owner of two tons of LEGO bricks. (This is about 4400 pounds.) He wrote, "[L]esson 1: if you win almost all bids you are bidding too high."

Mattheij had noticed that bulk, unsorted bricks sell for something like €10/kilogram, whereas sets are roughly €40/kg and rare parts go for up to €100/kg. Much of the value of the bricks is in their sorting. If he could reduce the entropy of these bins of unsorted bricks, he could make a tidy profit. While many people do this work by hand, the problem is enormous—just the kind of challenge for a computer. Mattheij writes:

There are 38000+ shapes and there are 100+ possible shades of color (you can roughly tell how old someone is by asking them what lego colors they remember from their youth).

In the following months, Mattheij built a proof-of-concept sorting system using, of course, LEGO. He broke the problem down into a series of sub-problems (including "feeding LEGO reliably from a hopper is surprisingly hard," one of those facts of nature that will stymie even the best system design). After tinkering with the prototype at length, he expanded the system to a surprisingly complex system of conveyer belts (powered by a home treadmill), various pieces of cabinetry, and "copious quantities of crazy glue."

Here's a video showing the current system running at low speed:

The key part of the system was running the bricks past a camera paired with a computer running a neural net-based image classifier. That allows the computer (when sufficiently trained on brick images) to recognize bricks and thus categorize them by color, shape, or other parameters. Remember that as bricks pass by, they can be in any orientation, can be dirty, can even be stuck to other pieces. So having a flexible software system is key to recognizing—in a fraction of a second—what a given brick is, in order to sort it out. When a match is found, a jet of compressed air pops the piece off the conveyer belt and into a waiting bin.

After much experimentation, Mattheij rewrote the software (several times in fact) to accomplish a variety of basic tasks. At its core, the system takes images from a webcam and feeds them to a neural network to do the classification. Of course, the neural net needs to be "trained" by showing it lots of images, and telling it what those images represent. Mattheij's breakthrough was allowing the machine to effectively train itself, with guidance: Running pieces through allows the system to take its own photos, make a guess, and build on that guess. As long as Mattheij corrects the incorrect guesses, he ends up with a decent (and self-reinforcing) corpus of training data. As the machine continues running, it can rack up more training, allowing it to recognize a broad variety of pieces on the fly.

Here's another video, focusing on how the pieces move on conveyer belts (running at slow speed so puny humans can follow). You can also see the air jets in action:

In an email interview, Mattheij told Mental Floss that the system currently sorts LEGO bricks into more than 50 categories. It can also be run in a color-sorting mode to bin the parts across 12 color groups. (Thus at present you'd likely do a two-pass sort on the bricks: once for shape, then a separate pass for color.) He continues to refine the system, with a focus on making its recognition abilities faster. At some point down the line, he plans to make the software portion open source. You're on your own as far as building conveyer belts, bins, and so forth.

Check out Mattheij's writeup in two parts for more information. It starts with an overview of the story, followed up with a deep dive on the software. He's also tweeting about the project (among other things). And if you look around a bit, you'll find bulk LEGO brick auctions online—it's definitely a thing!

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Nick Briggs/Comic Relief
What Happened to Jamie and Aurelia From Love Actually?
May 26, 2017
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Nick Briggs/Comic Relief

Fans of the romantic-comedy Love Actually recently got a bonus reunion in the form of Red Nose Day Actually, a short charity special that gave audiences a peek at where their favorite characters ended up almost 15 years later.

One of the most improbable pairings from the original film was between Jamie (Colin Firth) and Aurelia (Lúcia Moniz), who fell in love despite almost no shared vocabulary. Jamie is English, and Aurelia is Portuguese, and they know just enough of each other’s native tongues for Jamie to propose and Aurelia to accept.

A decade and a half on, they have both improved their knowledge of each other’s languages—if not perfectly, in Jamie’s case. But apparently, their love is much stronger than his grasp on Portuguese grammar, because they’ve got three bilingual kids and another on the way. (And still enjoy having important romantic moments in the car.)

In 2015, Love Actually script editor Emma Freud revealed via Twitter what happened between Karen and Harry (Emma Thompson and Alan Rickman, who passed away last year). Most of the other couples get happy endings in the short—even if Hugh Grant's character hasn't gotten any better at dancing.

[h/t TV Guide]